Optimizing Maize Yield under Subsurface Drip and Deficit Irrigation using Sowing Date and Temperature in CropSyst

Year 2025, Volume: 9 Issue: 3, 690 - 705, 27.09.2025

Taofeek Samuel Wahab , Alkhan Sarıyev , Mert Acar , Celaleddin Barutçular , Ahmet Çilek

https://doi.org/10.31015/2025.3.7

Abstract

Optimizing agricultural output through modeling can aid in planning, reduce the environmental impacts of agricultural activities, and enhance yields under deficit agricultural inputs. Climatic and agronomic data were collected from three subsurface irrigation regimes (I100 irrigation to field capacity (FC), I75 irrigation to 75% FC and I50 irrigation to 50% FC) over three years (2017–2019) at Cukurova University Agricultural Experimental Station. The treatments were applied in a completely randomized block design with three replications. 2019 data was used for model calibration, and 2017 and 2018 data were used for validation. Optimization involved adjusting the sowing date backward and manipulating temperature levels. The Cropping Systems Simulation Model (CropSyst) was successfully calibrated, except for the I50 Leaf area index (LAI), having a low regression coefficient and high root mean square error, an indication that CropSyst may not accurately simulate LAI at low deficit irrigation (DI). Promising results were obtained through sowing date optimization, particularly with I50 exhibiting the greatest yield improvement. Altering the average atmospheric temperature by a few degrees did not negatively affect I100, while DI applications resulted in yield loss at temperatures higher than 30 °C. CropSyst could not estimate maize yield at extreme temperatures for all treatments (above 40 °C) during the anthesis stage, indicating that the model may not be sensitive to certain maize growth stages. The optimization results indicate that for DI regimes to be competitively adopted as an alternative strategy for irrigation water conservation, the appropriate sowing date or temperature range must be carefully considered.

Keywords

Calibration , Crop growth , Crop modeling , Simulation , Soil water management

Supporting Institution

The Research Foundation of Cukurova University

Project Number

This study was supported by the Scientific Research Projects Unit of Çukurova University. Project number: FYL-2019-12298

Thanks

Thank you for taking your time to examine this manuscript

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