Paddy rice is the staple food in Taiwan, where rice farming always plays an important role in agricultural activities. The paddy fields and irrigation activities hold diversified functions, such as production, eco-environmental and living-associated functions. This paper is to provide information regarding the potential magnitude and monetary value of seven functions of paddy fields in Taiwan, including flood mitigation, fostering water resources, preventing soil erosion, purifying water, cooling air temperature, refreshing atmosphere and recreation. For quantification of the above values, replacement cost method (RCM), contingent valuation method (CVM), and the travel cost method (TCM) are adopted. In addition, the ratio of monetary value and their rice production commodity value (R) was also estimated. The results indicated that the flood mitigation function had a monetary value of US$ 389 million each year, and the ratio to the rice production value R was estimated at 37%.

Flooded paddy fields have many functions, including not only rice production, and ecological and environmental conservation. This work estimates the extent of paddy field infiltration in Taiwan by adopting a one-dimensional Darcy-based soil/water balance model SAWAH (Simulation Algorithm for Water Flow in Aquatic Habitats). A 10cm thick plow sole layer with a hydraulic conductivity of 0.03 cm/day, coupled with the soil texture and irrigation data obtained from 15 irrigation associations, is used to estimate the volumetric amount of annual infiltration in Taiwan. Simulation results from SAWAH indicate that the plow sole layer controls the movement of infiltrated water, with a rate about 1.8 billion cubic meters annually. The estimated infiltration rate of 1.8 billion m 3 /yr comprises more than 40% of the annual infiltration recharge to ground water in Taiwan.

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The study compared the climate indices and considered the major agricultural climate features, including precipitation, temperature, solar duration, radiation, and uncertainty features such as the ENSO and rainfall extremes, to compose the climate indices for rice production in Taiwan. The study used the regression model for panel data random effects, estimated rice-climatic indices for the first and second rice crop yields, and based on the results to provide specific policy recommendations.