Simulation of Irrigation Strategy Based on Stochastic Rainfall and Evapotranspiration

Abstract

The North China Plain plays a pivotal role in China’s crop production, contributing to 30% of the maize yield. Nevertheless, summer maize in this region faces challenges due to climatic constraints characterized by concurrent high temperatures and rainfall during the growing season, resulting in a relatively high evapotranspiration rate. In this study, we explored eight soil moisture-based threshold irrigation strategies, consisting of two upper limits and four lower limits, along with a rainfed mode (E). The upper and lower irrigation limits are expressed as a percentage of the field’s water-holding capacity (sfc). For the four full irrigation modes (A1, A2, A3, A4), the lower limits were set at 0.6 sfc, 0.6 sfc, 0.5 sfc, and 0.5 sfc, respectively. The upper limits were defined at two levels: 0.8 sfc for A1 and A2 and sfc for A3 and A4. Similarly, for the four deficit irrigation modes (B1, B2, B3, B4), the lower limits were established at 0.4 sfc, 0.4 sfc, 0.3 sfc, and 0.3 sfc, respectively, with the upper limits set at two levels: 0.8 sfc for B1 and B2 and the full sfc for B3 and B4. To investigate the impact of rainfall and potential evapotranspiration on these irrigation modes under long-term fluctuations, we employed a stochastic framework that probabilistically linked rainfall events and irrigation applications. The Monte Carlo method was employed to simulate a long-term series (4000a) of rainfall parameters and evapotranspiration using 62 years of meteorological data from the Xinxiang region, situated in the southern part of the North China Plain. Results showed that the relative yield and net irrigation water requirement of summer maize decreased with decreasing irrigation lower limits. Additionally, the interannual variation of rainfall parameters and evapotranspiration during the growing season were remarkable, which led to the lowest relative yield of the rainfed mode (E) aligned with a larger interannual difference. According to the simulation results, mode A4 (irrigation lower limit equals 0.5 sfc, irrigation upper limit equals 0.8 sfc) could be adopted for adequate water resources. Conversely, mode B2 is more suitable for a lack of water resources.

Keywords

• irrigation strategy
• stochastic precipitation
• evapotranspiration
• soil moisture probability density function
• irrigation requirement
• Monte Carlo method