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Your search keyword '"Farmaha, Bhupinder S."' showing total 2 results
Start Over Author "Farmaha, Bhupinder S." Topic spatial variability
2 results on '"Farmaha, Bhupinder S."'

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

Author

Farmaha, Bhupinder S., Pritpal-Singh, and Bijay-Singh

Subjects
*WHEAT, *GEOGRAPHIC information systems, *STANDARD deviations, *WETLANDS, *PLANT-water relationships, *GROUNDWATER pollution
Abstract

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. [ABSTRACT FROM AUTHOR]

Published
2021
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2. Assessing explanatory factors for variation in on-farm irrigation in US maize-soybean systems

Author

Haishun Yang, Patricio Grassini, Katherine E.B. Gibson, Trenton E. Franz, Paolo Nasta, Bhupinder S. Farmaha, John B. Gates, Dean E. Eisenhauer, Gibson, Katherine E. B., Yang, Haishun S., Franz, Trenton, Eisenhauer, Dean, Gates, John B., Nasta, Paolo, Farmaha, Bhupinder S., and Grassini, Patricio

Subjects
Irrigation, 010504 meteorology & atmospheric sciences, 0208 environmental biotechnology, Deficit irrigation, Soil Science, 02 engineering and technology, 01 natural sciences, Crop, Soil, Evapotranspiration, Precipitation, Weather, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, Spatial variation, Risk aversion, Irrigation statistics, Maize, On-farm data, 020801 environmental engineering, Agronomy, Environmental science, Spatial variability, Soybean, Agronomy and Crop Science
Abstract

Irrigation exhibits large variation across producer fields, even within same region and year. A knowledge gap exists relative to factors that explain this variation, in part due to lack of availability of high-quality irrigation data from multiple field-years. This study assessed sources of variation in irrigation using a large database collected during 9 years (2005–2013) from ca. 1400 maize and soybean producer fields in Nebraska, central USA (total of 12,750 field-year observations). The study area is representative of ca. 4.5 million ha of irrigated land sown with maize and soybean. Influence of biophysical (weather, soil, and crop type) and behavioral (producer skills, risk aversion) factors on irrigation was investigated. Field irrigation distributions showed a substantial number of fields received irrigation amounts that were well above average irrigation for same region-year. Variation in irrigation across fields, within the same region, was as large as year-to-year variation. Seasonal water deficit (defined as total reference evapotranspiration minus precipitation), soil available water holding capacity, and crop type explained about half of observed variation in field irrigation, indicating that producers adjusted irrigation depending upon site-year variation in these parameters. However, half of the variation in irrigation remained unexplained, indicating that producer behavior and skills play also an important role. There was evidence of a “neighbor” effect as fields that received large irrigation were surrounded by other fields with similarly large irrigation. Likewise, fields with above- or below-average irrigation in one year remained consistently above and below regional average irrigation, respectively, in other years despite similarity in weather and soil among fields. These findings indicate that irrigation decisions are influenced by both biophysical and behavioral factors, making predictions of field and regional irrigation extremely difficult. This study highlights the value of collecting on-farm irrigation data to understand producer decision-making and find opportunities to improve current water management in irrigated crop systems.

Published
2018

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