Abstract

The lack of coupled surface-subsurface flow models applied in lowland rice irrigation systems is the prime mover for this research. This study aimed to develop a coupled model that can capture the soil-water dynamics in paddy rice fields and to calibrate and validate the model using actual field data to serve as basis for irrigation water management using alternate wetting and drying (AWD) for lowland rice production systems. The zero-inertia surface flow model was internally coupled with the Richards-based subsurface flow model through Python scripts. Boundary conditions were set accordingly based on lowland rice field scenarios. Irrigation advance times were observed manually, while field water recession data were collected using wireless sensors. Model calibration showed acceptable results for the surface flow (R2≥0.99; SE≥0.97; RMSE≤3.14min), and subsurface flow (R2≥0.71; NSE≥0.60; MSE≤8.78mm; SD≤5.51mm; AE≤7.51mm) domains. Likewise, model validation yielded acceptable results for surface flow (R2≥0.98; NSE≥0.88; RMSE≤6.12min) and subsurface flow (R2≥0.76; NSE≥0.60; RMSE≤10.87mm; SD≤7.91mm; AE≤8.28mm), respectively. Results also showed the model’s capability to simulate water level fluctuations in AWD-irrigated rice fields during the wet and dry seasons under various rainfall scenarios. Model projections showed the need for AWD irrigation practice when the normal rainfall had been reduced by 75% during the wet season. Dry season simulations indicated the need for AWD under all rainfall scenarios. Simulation results have further unveiled the importance of the plow pan characteristics in influencing the soil-water flow behavior. This study was also able to address the limitations of the existing coupled models that could not meet the boundary conditions of paddy rice field settings. Ultimately, the model developed in this study could serve as basis for the development of optimum irrigation operation schemes in AWD -irrigated rice fields.

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