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Effect of Low Water Temperature on Rice Yield in California

^a Graduate Group in Ecology, Univ. of California, Davis, CA 95616 (present address: Instituto Nacional de Investigación Agropecuaria, Treinta y Tres, Uruguay)
^b Univ. of California Coop. Ext., Oroville, CA 95965
^c Dep. of Agronomy and Range Science and Dep. of Biological and Agricultural Engineering, Univ. of California, Davis, CA 95616

View larger version (15K): [in a new window]   Fig. 1. Sensor deployment in both (a) Field 1 and (b) Field 2. Arrows indicate water intake and flows.

View larger version (26K): [in a new window]   Fig. 2. Temperature record from sensors located in the coldest (Sensor 12) and warmest (Sensor 26) parts of Field 1 in 2001. The pattern from Field 2 was similar except that all temperatures were warmer and oscillations at the end of the season tended to be much smaller.

View larger version (15K): [in a new window]   Fig. 3. Plots of the data for Field 1 for the value of Tb that provided the best fit. In each curve the solid line is the simple linear regression and the dashed line is the best fitting exponential model.

View larger version (13K): [in a new window]   Fig. 4. Plots of the data for Field 2 for the value of Tb that provided the best fit. In each curve the solid line is the simple linear regression.

View larger version (13K): [in a new window]   Fig. 5. Plot of the aggregated data for Tb = 20°C of all field–year combinations. The solid curve is the best fit of the modified logistic equation of the form of Eq. [1] in the text.