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Anil, A.S., Sharma, V.K., Jimenez-Ballesta, R., Parihar, C.M., Datta, S.P., Barman, M., Chobhe, K.A., Kumawat, C., Patra, A. & Jatav, S.S. 2022. Land. 11 (9). Article number 1488 https://doi.org/10.3390/land11091488
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Dey, A., Patel, S. & Singh, H.P. 2022. Pages 204-218. In. Kumar, P., Pandey, S.K., Singh, S.K., Singh, S.S. & Singh, V.K. (Eds.) Sustainable Agriculture Systems and Technologies. John Wiley & Sons. Chichester, UK. 376 pages. https://doi.org/10.1002/9781119808565.ch9
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This paper presents an approach that integrates long-term field experimental data and modeling to quantify resilience of NT at a watershed scale in Michigan. Recharge, groundwater table, soil moisture, yield, and net return were used as resilience metrics. The DSSAT sequence crop model was developed for a corn-soybean-wheat rotation and calibrated using the yield and soil moisture data from a long-term (1993–2019) experiment for the conventional and the no-till treatment conducted within the study area. Their results show evidence of higher recharge and net return under the no-till treatment, which were statistically significant for all crops at the watershed scale. The NT treatment also retained more soil moisture that helped mitigate drought impacts. The groundwater table also rose in NT treatments.