Modelling crop yield, soil water content and soil temperature for a soybean-maize rotation under conventional and conservation tillage systems in Northeast China.
Liu, S., Yang, J.Y., Zhang, X.Y., Drury, C.F., Reynolds, W.D., and Hoogenboom, G. (2013). "Modelling crop yield, soil water content and soil temperature for a soybean-maize rotation under conventional and conservation tillage systems in Northeast China.", Agricultural Water Management, 123, pp. 32-44. doi : 10.1016/j.agwat.2013.03.001 Access to full text
Soil-crop simulation models can be a valuable tool in evaluating conservation tillage practices which are viable both economically and environmentally. The objective of this study was to evaluate the ability of the DSSAT (Decision Support Systems for Agro-technology Transfer) Cropping System Model (CSM) with the CSM-CROPGRO-Soybean and CSM-CERES-Maize modules to predict crop yields and root zone soil water and temperature dynamics for a soybean (Glycine max)–maize (Zea mays) rotation under conventional tillage (CT), reduced conventional tillage (RT) and no-tillage (NT) on a cool, semi-arid “Black soil” (Mollisol) in Northeastern China. Crop yield, soil water content and soil temperature data collected from a field experiment at Hailun Experimental Station (47°26′N, 126°38′E) during 2004–2011 were used for model calibration and evaluation. The soybean and maize cultivar coefficients were calibrated using the CT yield data, and evaluated using the RT and NT yield data. “Good” agreement between simulated and measured yields was achieved for model calibration (normalized Residual Mean Square Error, nRMSE = 9–15%), and “good” to “moderate” agreement was achieved for model evaluation (nRMSE = 12–17%). Simulated volumetric soil water content in the top 20 cm of CT, RT and NT were in “moderate” to “good” agreement with measurements (index of agreement, d = 0.81–0.91; nRMSE = 15.3–20.0%), provided that non-destructive in situ measurements of water content were used. Overall agreement between measured and simulated soil temperature varied from “poor” to “excellent” depending on year and tillage; and the measured soil temperatures were consistently overestimated (mean error, E = 3.2–6.2), possibly due to lack of accounting in DSSAT for the insulating effects of accumulated surface residues, and the shading effects of standing crops. Refinement of the soil temperature algorithm in DSSAT is recommended.
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