: Saturated soil culture is one of the water saving techniques that can improve water productivity. However, it is either less implemented or adopted because it consumes more time and energy. Therefore, an experiment was conducted to determine the effective water depth that can keep soil moisture close to saturation for a commonly practiced irrigation interval, combined with a rainfall pattern for increasing water productivity. The design was a randomized complete block with three replications and four water treatments representing 120% (T120), 180% (T180), 240% (T240), and 300% (T300) of soil saturation or the application of 2, 3, 4 and 5 cm water depth. The results showed that the application of 3 cm was the effective depth. It decreased plant height, tiller number, chlorophyll content, and panicle number per hill by 12.37%, 20.84%, 7.59%, and 70.98%, respectively. The decrease of these parameters is followed by total recovery due to effective rainfall contribution, which led to low yield sacrifice (6% of reduction) and 40% of water saving. We argue that weekly application of a 3 cm water depth and matching crop needed-water period with the onset of rainfall may be implemented and recommended as suitable saturated soil culture practice for rice production in high water demand conditions.

This study aimed to determine the highly sensitive variables for a groundwater simulation model adjacent to an artificial recharge lake (ARL) using short-term rainfall events. The model was established using an artificial neural network (ANN) with rainfall events. Normalized rainfall, rainfall intensity, and groundwater data were selected as model variables. The coefficient of determination (R²) was used for model performance assessment. Finally, a sensitivity analysis (SA) was conducted to evaluate the importance of each model input. The study results indicated that the R² of the ANN model ranged between 0.759 and 0.914. The SA showed that the rainfall was more sensitive than rainfall intensity in the study area. Based on the SA results and relevant geological characteristics, it was observed that the rainfall of past 1-day, past 2-day, and past 3-day responded faster than the other variables to the wells near the river and the ARL. In addition, the past 2-day rainfall was highly sensitive to the groundwater table; this may be due to the fact that the well screen location was above sea level as observed in Wells 1, 2, and 6. The results indicate that the groundwater table variation is response-related to the distance from the wells to the river and the ARL, and the rainfall time-lag. This SA study is helpful to researchers wishing to study related ARL efficiency issues.