Spatial and Temporal Assessment of Nitrate-N under Rice-Wheat System in Riparian Wetlands of Punjab, North-Western India

被引:13
|
作者
Farmaha, Bhupinder S. [1 ]
Pritpal-Singh [2 ]
Bijay-Singh [3 ]
机构
[1] Clemson Univ, Dept Plant & Environm Sci, Edisto Res & Educ Ctr, Blackville, SC 29817 USA
[2] Punjab Agr Univ, Dept Soil Sci, Khokhar Khurd 151505, Punjab, India
[3] Punjab Agr Univ, Dept Soil Sci, Ludhiana 141004, Punjab, India
来源
AGRONOMY-BASEL | 2021年 / 11卷 / 07期
基金
美国食品与农业研究所;
关键词
ANIMO model; GIS; groundwater; nitrate leaching; spatial variability; riparian wetlands; NITROGEN DYNAMICS; ANIMO MODEL; SIMULATION; SOIL; FERTILIZATION; CONTAMINATION; GROUNDWATER; TRANSPORT; REGION;
D O I
10.3390/agronomy11071284
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
The nitrate (NO3-) leaching assessment from extensive fertilizer nitrogen (N) applications to croplands is crucial to optimize fertilizer-N recommendations that do not threaten the quality of drinking groundwater. SWAP (Soil Water Atmosphere Plant), a water balance model, was linked with ANIMO (Agricultural NItrogen MOdel), a nitrate leaching model and the Geographical Information System (GIS) to assess the spatial and temporal leaching of NO3--N from fields under rice-wheat cropping system in the riparian wetlands in the Punjab in north-western India. The results revealed that NO3--N concentration in the groundwater exceeded the 10 mg NO3--N L-1 limit set by the World Health Organization (WHO) for drinking water only during December-January. The verification of these results using measured values indicated that the SWAP-ANIMO model satisfactorily predicted NO3--N concentrations in the leachate in the vadose zone. A low value of the mean absolute error (0.5-1.4) and a root mean square error (0.6-1.5) was observed between the measured and the predicted NO3--N concentration across the soil profile during the validation at five sampling sites. The NO3--N predictions revealed that in the long-term, the ongoing fertilizer-N management practices in the riparian wetlands will not significantly change the average NO3--N concentration in the groundwater. The modeling approach was satisfactory for an efficient quantitative assessment of NO3--N pollution in groundwater while accounting for the spatial and temporal variability.
引用
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页数:17
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