Simulating plastic mulching effects on the soil water balance and maize yields using the modified RZ-SHAW model

Authors: ZHOU, LIFENG - Kunming University Of Science And Technology; ZHANG, HAO - Northwest A&f University; Ma, Liwang; SIDDQUE, KADAMBOT - Northwest A&f University; FENG, HAO - Northwest A&f University

Submitted to: Field Crops Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/11/2025
Publication Date: 12/14/2025
Citation: Zhou, L., Zhang, H., Ma, L., Siddque, K., Feng, H. 2025. Simulating plastic mulching effects on the soil water balance and maize yields using the modified RZ-SHAW model. Field Crops Research. Article 109712. https://doi.org/10.1016/j.fcr.2024.109712.
DOI: https://doi.org/10.1016/j.fcr.2024.109712

Interpretive Summary: Optimizing irrigation efficiency is vital for water management in the arid regions of China. Mulched drip irrigation (MDI) is a prevalent practice to ensure agricultural production by covering the soil surface to reduce evaporation. Most agricultural models inadequately account for the effects of mulching on irrigation efficiency. We addressed this knowledge gap by integrating a plastic mulch module (PM) into the RZSHAW model (RZ-SHAW-PM). The plastic mulch module incorporates the effects of plastic film mulching on net radiation, sensible and latent heat fluxes, and rainfall interception through plastic-residue layers. We assessed the model’s performance in simulating soil water content (SWC), soil evaporation (Es), evapotranspiration (ET), leaf area index (LAI), dry biomass (DM), and grain yield of maize using three years (2014-2016) of field data, encompassing NM (no mulching), M1 (full soil mulching), and M0.6 (partial soil mulching with a fraction cover of 0.6) treatments. The RZ-SHAW-PM model adequately simulated SWC in the NM and both mulching treatments, with an acceptable simulation of Es and ET over the entire maize growing season. However, the model overestimated Es during early growth (0-80 days after sowing) and underestimated Es during later growth (80-140 days after sowing) in all treatments. Moreover, the RZ-SHAW-PM model overestimated ET over the entire growing season in the NM treatment but underestimated ET during early growth and overestimated ET during later growth in the mulching treatments. Overall, the RZ-SHAW-PM model effectively captured the responses of crop water and nitrogen stress to mulching, irrigation, and fertilization. Therefore, it is a promising tool for guiding irrigation and fertilization strategies in MDI systems, and optimizing crop production in arid regions.

Technical Abstract: Agricultural system models are practical tools for optimizing irrigation and fertilization strategies. Mulched drip irrigation (MDI) is a prevalent practice in arid regions, playing a vital role in ensuring agricultural production by improving soil water and heat conditions. However, existing agricultural models inadequately account for the effects of MDI on land surfaces, limiting their effectiveness in guiding irrigation and fertilization practices. We addressed this gap by integrating a plastic mulch module into the RZSHAW model (RZ-SHAW-PM). The plastic mulch module incorporates the effects of plastic film mulching on net radiation, sensible and latent heat fluxes, and rainfall interception through plastic-residue layers. We assessed the model’s performance in simulating soil water content (SWC), soil evaporation (Es), evapotranspiration (ET), leaf area index (LAI), dry biomass (DM), and grain yield of maize using three years of field trial data, encompassing NM (no mulching), M1 (full soil mulching), and M0.6 (partial soil mulching with a fraction cover of 0.6) treatments. The RZ-SHAW-PM model adequately simulated SWC with root mean squared errors (RMSE) between 0.009 cm3/cm3 and 0.018 cm3/cm3 in the NM, and 0.007 cm3/cm3 to 0.031 cm3/cm3 in the mulch treatments. Similarly, an acceptable simulation of Es (RMSE=0.12 mm - 0.20 mm) and ET (RMSE= 0.26 mm - 0.73 mm) was obtained for all treatments over the entire maize growing season. However, the model overestimated Es during early growth (0-80 days after sowing) and underestimated Es during later growth (80-140 days after sowing) in all treatments. Moreover, the RZ-SHAW-PM model overestimated ET over the entire growing season in the NM treatment but underestimated ET during early growth and overestimated ET during later growth in the mulching treatments. Despite these nuances, the RZ-SHAW-PM model effectively captured the responses of crop water and nitrogen stress to mulching, irrigation, and fertilization, with RMSE between 0.15 and 0.26 for LAI, 0.51 t/ha to 2.12 t/ha for DM, 0.22 t/ha to 2.78 t/ha for grain yield. Overall, our findings suggest that the RZ-SHAW-PM model is a promising tool for guiding irrigation and fertilization strategies in MDI systems, and optimizing crop production in arid regions.